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This paper aims to address the challenges in hydroacoustic signal detection, signal distortion and target localization caused by baseline drift. The authors propose a combined algorithm that integrates short-time Fourier transform (STFT) detection, smoothness priors approach (SPA), attitude calibration and direction of arrival (DOA) estimation for micro-electro-mechanical system vector hydrophones.

Initially, STFT method screens target signals with baseline drift in low signal-to-noise ratio environments, facilitating easier subsequent processing. Next, SPA is applied to the screened target signal, effectively removing the baseline drift, and combined with filtering to improve the signal-to-noise ratio. Then, vector channel amplitudes are corrected using attitude correction with 2D compass data. Finally, the absolute target azimuth is estimated using the minimum variance distortion-free response beamformer.

Simulation and experimental results demonstrate that the SPA outperforms high-pass filtering in removing baseline drift and is comparable to the effectiveness of variational mode decomposition, with significantly shorter processing times, making it more suitable for real-time applications. The detection performance of the STFT method is superior to instantaneous correlation detection and sample entropy methods. The final DOA estimation achieves an accuracy within 2°, enabling precise target azimuth estimation.

To the best of the authors’ knowledge, this study is the first to apply SPA to baseline drift removal in hydroacoustic signals, significantly enhancing the efficiency and accuracy of signal processing. It demonstrates the method’s outstanding performance in the field of underwater signal processing. In addition, it confirms the reliability and feasibility of STFT for signal detection in the presence of baseline drift.

Ciliated microelectromechanical system (MEMS) vector hydrophones pick up sound signals through Wheatstone bridge in cross beam-ciliated microstructures to achieve information transmission. This paper aims to overcome the complexity and variability of the marine environment and achieve accurate location of targets. In this paper, a new method for ocean noise denoising based on improved complete ensemble empirical mode decomposition with adaptive noise combined with wavelet threshold processing method (CEEMDAN-WT) is proposed.

Based on the CEEMDAN-WT method, the signal is decomposed into different intrinsic mode functions (IMFs), and relevant parameters are selected to obtain IMF denoised signals through WT method for the noisy mode components with low sample entropy. The final pure signal is obtained by reconstructing the unprocessed mode components and the denoising component, effectively separating the signal from the wave interference.

The three methods of empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD) and CEEMDAN are compared and analyzed by simulation. The simulation results show that the CEEMDAN method has higher signal-to-noise ratio and smaller reconstruction error than EMD and EEMD. The feasibility and practicability of the combined denoising method are verified by indoor and outdoor experiments, and the underwater acoustic experiment data after processing are combined beams. The problem of blurry left and right sides is solved, and the high precision orientation of the target is realized.

This algorithm provides a theoretical basis for MEMS hydrophones to achieve accurate target positioning in the ocean, and can be applied to the hardware design of sonobuoys, which is widely used in various underwater acoustic work.

This paper aims to solve the problems of baseline drift, susceptibility to abnormal data interference during baseline drift processing, and phase inconsistency in underwater acoustic target detection and signal processing of single microelectromechanical systems (MEMS) vector hydrophone. To this end, this paper proposes a baseline drift removal algorithm based on Huber regression model with B-spline interpolation (H-BS) and a phase compensation algorithm based on the Hilbert transform.

First, the Huber regression model is innovatively introduced into the conventional B-spline interpolation (B-spline) to solve the control point vectors more accurately and to improve the anti-interference ability of the abnormal data when the B-spline interpolation fitting removes baseline drift and the baseline drift components in the signals are fitted accurately and removed by the above method. Next, the Hilbert transform is applied to the three-channel output signals of the MEMS vector hydrophone to calculate the instantaneous phase and the phase compensation is performed on the vector X/Y signals with the scalar P signal as the reference.

Through simulation experiments, it is found that H-BS proposed in this paper has smaller processing error and better robustness than variational modal decomposition and B-spline, but the H-BS algorithm takes slightly longer than the B-spline. In the actual lake test experiments, the H-BS algorithm can effectively remove the baseline drift component in the original signal and restore the signal waveform, and after the Hilbert transform phase compensation, the direction of arrival estimation accuracy of the signal is improved by 1°∼2°, which realizes high-precision orientation to the acoustic source target.

In this paper, the Huber regression model is introduced into B-spline interpolation fitting for the first time and applied in the specialized field of hydroacoustic signal baseline drift removal. Meanwhile, the Hilbert transform is applied to phase compensation of hydroacoustic signals. After simulation and practical experiments, these two methods are verified to be effective in processing hydroacoustic signals and perform better than similar methods. This study provides a new research direction for the signal processing of MEMS vector hydrophone, which has important practical engineering application value.

In acoustic detection technology, optical microcavities offer higher detection bandwidth and sensitivity than traditional acoustic sensors. However, research on acoustic detection technologies involving optical microcavities has not yet been reported. Therefore, this paper aims to design and construct an underwater acoustic detection system based on optical microcavities and study its acoustic detection technology to improve its performance.

Based on the principles of optical microcavity acoustic sensors, a signal-detection circuit was designed to form a detection system in conjunction with a laser, an optical waveguide resonator and an oscilloscope. This circuit consists of two modules: a photodetection module and a filter amplification module.

The photodetection module features a baseline noise of −106.499 dBm and can detect device spectral line depths of up to 2410 mV. The gain stability of the filter amplification module was 58 dB ± 1 dB with a noise gain of −107.626 dBm. This design allows the acoustic detection system to detect signals with high sensitivity within the 10 Hz−1.2 MHz frequency band, achieving a maximum sensitivity of −126 dB re 1 V/µPa at 800 Hz and a minimum detectable pressure (MDP) of 0.37 mPa/Hz^1/2, corresponding to a noise equivalent pressure (NEP) of 51.36 dB re 1 V/µPa.

This study designs and constructs a broadband underwater acoustic detection system specifically for optical waveguide resonators based on the sensing principles of silicon dioxide optical waveguide resonators. Experiments demonstrated that the signal detection module improves the sensitivity of underwater acoustic detection based on optical waveguides.

The purpose of this paper is to investigate the friction and wear mechanisms in lubricated sliding conditions of additively manufactured SS316L parts. The different viscous oils 5W30, 15W40, 20W50 and SAE140 are used. These investigations provide a theoretical basis for the high performance of printed and postheattreated SS316L.

Tribological tests were carried out on selective laser melting-made SS316L printed specimens and heat-treated specimens. The parameters in 15 min of test duration are 20 N of load, 200 rpm, 8 mm of pin diameter, 25 mm length, 80 mm of track diameter and EN31 counter disc body. This work presented the phenomena of lubrication regimes and their characterization, as identified by the Stribeck curve, and these regimes affect the tribological properties of additively manufactured SS316L under the influence of industrial viscous lubricants. The results are observed using Scanning electron microscope (SEM), X-ray diffraction (XRD) and wear tests.

The observations indicate that additively manufactured SS316L shows a reduced coefficient of friction (COF) and specific wear rate (SWR). This is credited to the utilization of different viscous lubricants.

This exclusive research demonstrates how various viscous lubricants affect the COF and SWR of printed and post-heat-treated SS316L parts. Lambda (λ), lubricant film thickness (h₀), surface roughness and wear mechanisms are studied and reported.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2024-0110/